A diagnostic algorithm for distinguishing the eosinophilia-myalgia syndrome from fibromyalgia (FM) & chrmyofascial pain

OBJECTIVE: To develop a diagnostic algorithm for the
eosinophilia-myalgia syndrome (EMS) that complements the
existing case definition.

METHODS: We conducted a
retrospective study using data on 59 clinical and laboratory
variables from a consecutive referral cohort of 91 patients
with EMS meeting the Centers for Disease Control and
Prevention case definition. Ageand sex matched controls
included 93 patients with fibromyalgia and 99 patients with
chronic myofascial pain. The study period was March 1989 to
April 1992. Recursive partitioning was used tocreate a
diagnostic algorithm.

RESULTS: In the 283 case patients and
controls with disabling myalgias, 4 differentiating variables
identified patients with EMS: extremity edema, leukocyte count
>12.5 x 10(9)/l, dyspnea, and absence of arthralgias. These
4 variables form a diagnostic algorithm that has a
sensitivity of 95.6%, a specificity of 96.9%, and positive
and negative predictive values of 93.5 and 97.9%,

CONCLUSION:This algorithm is practical and can
be easily applied in any medical setting. It also readily
distinguishes EMS from other common myalgia syndromes.

MCM: Describes a computer-generated algorithm using presence
or absence of edema, leukocytosis, dyspnea, and arthraligias
to make this differentiation in 283 pts.

Taylor RM, Gabriel SE, O'Fallon WM, Bowles CA, Duffy J

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